[Graph][Fusion] Add QKVNormRope and QKVNormRopeWithBias (#5721)
### What this PR does / why we need it?
This PR builds upon PR
https://github.com/vllm-project/vllm-ascend/pull/5011 and aims to
further enhance the npu_graph_ex_passes module. Based on prior work, we
have added graph optimization support for the add_rms_quant fused
operator in scenarios where a bias term is present—ensuring the fusion
pattern is correctly registered and matched into the computation graph.
For validation, we switched to the Qwen3-235B-A22B-W8A8 model for
QKVNormRopeWithBias and Qwen3-32B model for QKVNormRope . Benchmark
results show that, compared to the unfused baseline, enabling this
fusion pass significantly improves inference throughput for W8A8
quantized models.
For more details can refer to the
RFC:https://github.com/vllm-project/vllm-ascend/issues/4715
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
```
llm = LLM(
model=model,
tensor_parallel_size=GPUs_per_dp_rank,
enforce_eager=False,
enable_expert_parallel=enable_expert_parallel,
trust_remote_code=trust_remote_code,
gpu_memory_utilization=0.98,
max_num_batched_tokens=512,
# load_format="dummy",
max_model_len=2048,
max_num_seqs=16,
quantization="ascend",
additional_config={
"refresh": True,
"enable_npugraph_ex": True
},
compilation_config={
"cudagraph_capture_sizes": [8, 16],
"cudagraph_mode": "FULL_DECODE_ONLY",
},
)
if profile_dir:
llm.start_profile()
outputs = llm.generate(prompts, sampling_params)
if profile_dir:
llm.stop_profile()
for i, output in enumerate(outputs):
if i >= 5:
break
prompt = output.prompt
generated_text = output.outputs[0].text
print(
f"DP rank {global_dp_rank}, Prompt: {prompt!r}, "
f"Generated text: {generated_text!r}"
)
```
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: cjian <2318164299@qq.com>
This commit is contained in:
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#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# This file is a part of the vllm-ascend project.
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#
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from torch._inductor.pattern_matcher import Match
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from vllm.logger import logger
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def extra_stream_scope_check(match: Match) -> bool:
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"""
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Checks if all nodes in the same stream.
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"""
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non_default_streams = set()
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has_default = False
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for node in match.nodes:
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if node.op == "call_function":
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current_stream = node.meta.get("stream_label")
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if current_stream is None:
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has_default = True
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else:
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non_default_streams.add(current_stream)
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if len(non_default_streams) > 1:
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logger.debug(
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f"Cross-stream operation detected in pattern match for AddRMSNormQuant. "
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f"Multiple streams found: {non_default_streams}. "
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f"Fusion is not supported for cross-stream operations."
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)
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return False
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if has_default and len(non_default_streams) > 0:
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logger.debug(
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f"Cross-stream operation detected in pattern match for AddRMSNormQuant. "
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f"Multiple streams found: {non_default_streams}. "
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f"Fusion is not supported for cross-stream operations."
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)
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return False
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return True
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